Within the field of art, many scenarios involve a task of classifying content items into one or more categories, such as identifying topics discussed in a message or document; objects present in an image; or a musical genre associated with a musical recording. These classification tasks may be performed by humans, e.g., by presenting the content items to users and receiving the categories identified by the users. These classification tasks may also be performed by an automated classifier, e.g., a Bayesian classification network or artificial neural network that is trained to classify content items into categories. This training is often performed, e.g., using a sample data set, such as a set of content items for which one or more categories have been previously identified. For example, an artificial neural network may be provided a set of content items for which the associated categories are known, and may therefore adjust the weights of the interconnections among the neurons in order to achieve a correct classification of the content items of the training set into the known categories. The artificial neural network, once trained, may be invoked to classify additional content items.